Platform, a Journal of Engineering (Sep 2022)
OPTIMIZATION OF RAW MIX DESIGN OF CLINKER PRODUCTION: A CASE STUDY IN CEMENT INDUSTRY
Abstract
Raw mix design refers to the raw materials' quantitative proportions to achieve clinker with the desired chemical and mineralogical composition. The existing method used to formulate the raw mix design is based on iterative laboratory trials, which is time-consuming and heavily relies on the chemist's experience. Considering the negative environmental impacts, optimizing the raw mix design has become one of the major concerns among the cement players. Thus, the objective of this research is to optimize raw mix design with minimum cost while satisfying the critical clinker quality control targets. This study explored the Linear Programming (LP) model to achieve the objective. A Series of mathematical modeling was developed to relate the decision variables, raw mix and fuel mix design and the clinker chemistry. Bogue calculation is then applied to correlate the oxides from both raw mix and fuel mix to the phase content of C3S, C2S, C3A and C4AF in the clinker. The ratio of the clinker phases would be Lime Saturation Factor (LSF), Silica Ratio (SR) and Alumina Modulus (AM), which are used to determine the quality of the clinker, were defined as the main constraint. Limitation in the plant design, such as the number of dosing weighers, is also considered programming constraint. A case study was performed with eight types of raw materials consisting of Limestone, clay, sand, alternate material and additives to evaluate the LP model. Based on the GRG Nonlinear LP simulation, the optimized raw mix design was achieved at the cost of RM 6.845 per tonne composed of, 85.03% of Limestone, 0.9% of Clay 1, 12.6% of Alternate Material 1 and 1.47% of Additive 2. The obtained results prove that the developed LP model can minimize the raw material cost save analysis time, and provide flexibility in the raw material selection process without the need for actual trials.
